WHITEPAPER

Modern Data Warehousing: Analytics without the Modeling

Eliminate the heavy lifting required to implement traditional data warehousesspeeding deployments and accelerating insights.

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WHITEPAPER

Data warehouses are great for supporting standard reporting and dashboard applications. But they are unwieldy if business users ask questions that weren’t modeled in the data warehouse to begin with. The time, money, and resources required to maintain a data warehouse to support ad-hoc queries and exploratory analysis is hard to justify.

Consequently, organizations are exploring new technologies, techniques, and tools that minimize the modeling required to modify data warehouses and support new analytical use cases.

Download this report to learn how companies are employing these three major approaches:

  • Big data techniques that leverage scale-out architectures
  • In-memory databases and caches combined with super-fast processors
  • Sophisticated data mapping algorithms that eliminate or minimize the need for upfront data modeling